2019
DOI: 10.1016/j.ecoenv.2019.109387
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Spatiotemporal variations and characterization of the chronic cancer risk associated with benzene exposure

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Cited by 12 publications
(9 citation statements)
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“…From the result of this study, the risk of developing cancer resulting from the exposure of chemical agents in the Kim-Kim River incident needs further investigation. However, a few studies have investigated the relationship between exposure to benzene and other volatile organic compounds (VOCs) [90,91]. Benzene exposure during childhood was associated with acute lymphocytic leukemia and acute myeloid leukemia of relative risk (RR) 1.0 (95% CI: 0.6-1.7) and RR 1.9 (95% CI: 0.3-11.1) [91].…”
Section: Cancermentioning
confidence: 99%
“…From the result of this study, the risk of developing cancer resulting from the exposure of chemical agents in the Kim-Kim River incident needs further investigation. However, a few studies have investigated the relationship between exposure to benzene and other volatile organic compounds (VOCs) [90,91]. Benzene exposure during childhood was associated with acute lymphocytic leukemia and acute myeloid leukemia of relative risk (RR) 1.0 (95% CI: 0.6-1.7) and RR 1.9 (95% CI: 0.3-11.1) [91].…”
Section: Cancermentioning
confidence: 99%
“…At this time, the advanced innovation state-space modeling framework by combining Box-Cox transformations, Fourier series with time-varying coefficients and autoregressive moving average (ARMA) error correction method (called TBATS) is tailored for extraction with the information included in a complex time series described above. 21 Furthermore, the TBATS approach can not only be used to deal with the linear issue but can handle some types of non-linearity based on Box-Cox transformations, 23 whilst allowing for time-dependent dynamic seasonality, 24 which enables this advanced method to have the potential to make a long-term forecast. Moreover, the TBATS approach also has a powerful ability to decompose a complex seasonal time series into constituent latent subseries, 21 which fails to be done by the aforementioned common methods.…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, the TBATS approach also has a powerful ability to decompose a complex seasonal time series into constituent latent subseries, 21 which fails to be done by the aforementioned common methods. In the past, the advanced TBATS model has been used to nowcast and forecast the flow time series in water distribution systems, 25 the demand for the electric energy, 26 and spatiotemporal variations and characterization of benzene, 23 and the resulting results indicated that this advanced method could produce a relatively high forecasting accuracy in these fields. However, there is no study to use this advanced method to analyze and evaluate the long-term epidemiological trends and seasonality of HFRS.…”
Section: Introductionmentioning
confidence: 99%
“…Re search on these relations is part of a broader trend that has been focusing on the search for any con nection between air pollution and cancer incidence and mortality (Chen et al 2016;Su et al 2019;Bai et al 2020). Additional analyses and metaanalyses were also carried out with the purpose of studying the risk of cancer being caused by benzene (Atabi and Mirzahosseini 2013;Kassomenos 2019, 2020;Sakizadeh 2019;Teras et al 2019) and fi nding any connections between benzene (present not only in the air) and leukaemia incidence and mortality, especially in children (Best et al 2001;Pyatt and Hays 2010;Filippini et al 2015;Janitz et al 2017;RaaschouNielsen et al 2018).…”
Section: Introductionmentioning
confidence: 99%